{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#引入numpy 库\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    " \n",
    "#引入matplotlib库\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "from matplotlib import cm\n",
    "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n",
    "\n",
    "\n",
    "from pylab import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#定义布尔值之间运算\n",
    "def otimes_b_b (a,b):\n",
    "    if a==b:\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#布尔向量定义为python中的列表 list\n",
    "\n",
    "#定义布尔向量与布尔值之间计算\n",
    "\n",
    "def otimes_bv_b(bv,b):\n",
    "    return [otimes_b_b(x,b) for x in bv]\n",
    "#定义布尔向量之间运算\n",
    "def otimes_bv_bv(bv1,bv2):\n",
    "    temp=[otimes_b_b(x,y) for x,y in zip(bv1,bv2)]\n",
    "    #如果两个向量之间相同位置布尔值相同的部分大于不同的部分\n",
    "    if temp.count(True)>temp.count(False):\n",
    "        #返回 True\n",
    "        return True\n",
    "    else:\n",
    "        #否则返回 False\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#矩阵定义为numpy中的array\n",
    "\n",
    "#定义布尔矩阵之间运算\n",
    "def otimes_bm_bm(bm1,bm2):\n",
    "    #后一个矩阵列向量变为行向量\n",
    "    bm2_t=np.transpose(bm2)\n",
    "    temp =[otimes_bv_bv(x,y) for x in bm1\n",
    "              for y in bm2_t]\n",
    "    temp =np.array(temp)  \n",
    "    return temp.reshape((bm1.shape[0],bm2.shape[1]))\n",
    "\n",
    "#定义矩阵与向量之间运算\n",
    "def otimes_bm_bv(bm,bv):\n",
    "    temp=[otimes_bv_bv(x,bv) for x in bm]\n",
    "    return temp\n",
    "\n",
    "#定义矩阵与布尔值之间计算\n",
    "def otimes_bm_b(bm,b):\n",
    "    temp=[otimes_bv_b(x,b) for x in bm]\n",
    "    return np.array(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "#随机向量与向量相乘\n",
    "a=np.random.rand(1,3)\n",
    "x=a>0.5\n",
    "vx=x[0].tolist()\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "for i in range(0,6):\n",
    "    y=np.random.rand(1,3)\n",
    "    y=y>0.5\n",
    "    vy=y[0].tolist()\n",
    "    fig,axs=plt.subplots(nrows=1, ncols=5, figsize=(12, 12))\n",
    "   \n",
    "    \n",
    "\n",
    "    res1=otimes_bv_bv(vy,vx)\n",
    "    res=np.array([[res1]])\n",
    "\n",
    "    #绘图表达\n",
    "    axs[0].imshow(y,vmin=0,vmax=1)\n",
    "    \n",
    "    axs[0].set_title(str(vy))\n",
    "    axs[0].set_axis_off()\n",
    "    \n",
    "    axs[1].imshow(op)\n",
    "    axs[1].set_axis_off()\n",
    "    \n",
    "    axs[2].imshow(x,vmin=0,vmax=1)\n",
    "    axs[2].set_title(str(vx))\n",
    "    axs[2].set_axis_off()\n",
    "    \n",
    "    axs[3].imshow(eq)\n",
    "    axs[3].set_axis_off()\n",
    "    \n",
    "    axs[4].matshow(res,vmin=0,vmax=1)\n",
    "    axs[4].set_title(str(res1))\n",
    "    axs[4].set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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00EMBmDlzJgBr1qwB4OKLL27az8knnwzAgw8+CMBNN90EwLJly5r2WyazkRLdfPPNAJx22mkAXHLJJUAj/Yo5wGH16tUAzJo1C4Ajjjiiab/lSnFlVYtB+cvzqmtj91rVtbeH6efbrs5vmZBGsrp8+XIALrrool43cUKtammX7S6PaxAT316/11f9WVr1Z1U/+2XV7wG9fo8a9HOxlcHr9ZIkSVKPOOdXlSjn+JZzYOP6vvvuCzTm5F5zzTUALFiwAGjM84vENxLcpUuXAo2kN9Kgsi5wzOWN9tx3331Ao95vzAGOKhJLliwB4Ktf/SrQSIgjQQ6x/zJtGpTEVyqV34qUfTTO5XK7QVnhrexbrebfl8fVajtJU5fJryRJkmrD5FeVKuf+lulNpEkrV64EGiuxxRzfZ599FmjM8T3zzDObHh/7Lef1bdmyBWgkweWKcVEf+JRTTgHgox/9aNPz7rfffgB87GMfAxrzCkN5HFHtIapFSIOmnH8f89PLqg9lQlp14hvKdpTtjONptVqjpPow+ZUkSVJt+CuvKhFJaaQukcqUNUYjkY2k9Stf+QrQSGA/8pGPAI05vvH4smpE+RffkfCWCXCZRMfKcLFqVCTC69evB2DOnDkAbN68GWhUpShF4hup06CkZVKIvhJ9sUxEy4oscQ63qqLQb9GeaF857778NmbQKq9I6h+TX0mSJNVG6udv64tHzpnwyaquN9drVdcMHZmzsWtx49jYWIZG2tLvJHPdunUAfOITnwDgoIMOAuDqq68GGnV3y/Sn1WpOZeL78MMPA/CZz3wGgE2bNgFw1VVXAbB48eKuHk875cp0IyMjXfmBd9onOz1ne/34Xuu0ffeO3drNjlNt9KquvZaD3i/bqbrfDlK/bPdatlP1uKGdQT/XWo17TH4lSZJUG8751VA68cQTAfjWt74FwNe+9jWgMRc47o+6vAcffDAAc+fOBRpJ9caNGwF4/PHHAbj77rsBuP/++wH4wAc+ADTmGh955JE9OR5JktQfJr+SJEmqDZNfDaWYo3vMMccAsGrVKgAeeOABAG6//XYArr/+egCef/55oFE9IubOzpgxA2isJHfUUUc17W/hwoVA69WtJEnScDH5lSRJUm2Y/GooRVWGSGKnTZsGwEknndR0GfdHUlwmv1HfNx7falUoE19JkqYGk19JkiTVxkAlv53Wi6u6nlynel3n+N6xjnY/UFqtqFau2lSu3jR79uym67HCW7vVn+Ky3Upuw6bqeqFV96lO3xOqrjOsqWnY+6X9YtcN+mtV9bnQq88Ik19JkiTVxkAlv9KuiuR169atwI4JbbmSW8wRLo2OjjZtX670FrfHnN+pkvhKklRXJr+SJEmqDZNfDaWYkzt9+nQAtm3bttPbQ1R3iO0iIY6V3iIhjsvYT1yPqhCxn3icJEkaLia/kiRJqg2TXw2lSGBDmdyGsmpDq0S4nOtbVn+I7Ux+JUkabia/kiRJqo2BSn6rrtNbdW3Cqmui7o4yYe23snpDmdS2uz1EgtuqGkS5XVWJb9XP30rVNSKrfs9op+r3FA2nquv4DvpnbdW1cbup6tdq0PXqtTT5lSRJUm04+JUkSVJtOPiVJElSbTj4lSRJUm04+JUkSVJtOPiVJElSbTj4lSRJUm0MVJ3fTnVau6/qmqSDVHtQ9VB1jcle16isuk9LvTDo/a7q95V22u3/3rHuPVfVx9rp8w96LffJMvmVJElSbTj4lSRJUm04+JUkSVJtTKk5v6qPnHOlz59SqvT5JUnS5Jj8SpIkqTZMfjWUTH4lSdJkmPxKkiSpNlLVCZokSZLULya/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaoNB7+SJEmqDQe/kiRJqg0Hv5IkSaqN/wfz2SNYpAtTaAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAACPCAYAAADz/LNqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4xLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvDW2N/gAAFAFJREFUeJzt3X+sXGWdx/H3c7GlbCs/1iJFNoC6hRSJSIloKj+FCkiBghYBK3Zh/1jXuKIJSnaNQSKiYnDZXTYbWBBDLIjgCghIG4TabOy6iOsaItgAK0Sk8qOEFCmt3Gf/6P3mME87nXLnx5m55/1KmmHmnjnnOZx5Zp77med+n5RzRpIkSWqCsbobIEmSJA2Kg19JkiQ1hoNfSZIkNYaDX0mSJDWGg19JkiQ1hoNfSZIkNYaDX0mSJDWGg98dlFK6P6W0PqW0c91tkSRp1KSUrk4pPZJSGk8pLau7PZqclNIBKaXbUkrPpJSeTyndk1I6sO52vR4OfndASml/4EggA6fW2hhJkmqSUnpDF0//JfC3wIM9ao660MW13B24HTgQ2Av4GXBbr9o1CA5+d8y5wBrgeuDj9TZFaraU0tsn0ob5E/ffklJ6NqV0TM1Nk6aklNL/pZQ+n1L6X+CllNK+KaVbJ5K/x1NKf/eabQ9PKT2QUnoxpbQupXRF/CznfFXO+V5gYx3nod5cy5zzz3LO1+acn885bwa+CRyYUnpTTaf1ujn43THnAt+Z+HdCSmmvmtsjNVbO+VHg88B3Ukp/BnwLuD7nfH+tDZOmtrOBk4E/B/6DLSnuPsBxwAUppRMmtrsSuDLnvCvwduDmGtqq7ev1tTwKeDrn/FxfW91DDn47SCkdAewH3Jxz/jnwKHBOva2Smi3nfA2wFvgvYG/gH+ptkTTl/VPO+UngYGDPnPMlOedNOefHgGuAsya22wz8ZUppds55Q855TV0NVls9u5Yppb8ArgI+O6jG94KD384+DqzIOT87cX85Tn2QhsE1bHnz/uec8yt1N0aa4p6cuN0PeEtK6YX4B/w9W+Z+ApwPHAA8nFL675TSohraqu3rybVMKe0JrAD+Ned844Da3hPdTFyf8lJKuwBnAjullJ6eeHhnYPeU0iE551/W1zqpuVJKs4B/BK4FLk4p3Zpzfr7mZklTWZ64fRJ4POc8d5sb5bwWODulNAacAdySUnpTzvmlAbVTnXV9LVNKe7Bl4Ht7zvnSgbS6h0x+t28x8CpwEPCuiX/zgNVsmQcsqR5XAj/POf81cCfwbzW3R2qKnwEvTvzR1C4ppZ1SSgenlN4NkFJamlLaM+c8Drww8ZxXJ342PaU0A0jAtJTSjImBleoxqWuZUtoVuAf4z5zzRTW1vSu+6Lbv48C3cs5P5Jyfjn/AvwAf7bLki6RJSCmdBpwI/M3EQ58F5qeUPlpfq6RmyDm/CpzCljDoceBZ4N+B3SY2ORF4KKW0gS2/pJ6Vc47qDiuAl4EFwNUT/33U4Fqv1+riWp4OvBv4q5TShtf823fgJzFJKefceStJkiRpCjD5lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjDLRU1/jTc7dbWuKEt7yrq/3f89T/dPX8TsfvtP9u299Jt8dfOf691MPm1FomZHx8vM7DMzZW+++NPbmWdffJuvtct+8Z3Rqbs3bK9En1pk8CLBxb0tdrWXe/6rbf91sv+2Wna1n3uKLf6n4ttLuWtX+CS5IkSYPiIg0aSSn1MjCTJElNYfIrSZKkxjD51Ugy+ZUkSZNh8itJkqTGcPArSZKkxnDwK0mSpMYY6JzfuuvVdXv8umuSDnttRE09ddegHPV6o51rb3e1e2mb+v1Z0O3+635f8bNyx9V9rfr1Hm3yK0mSpMZw8CtJkqTGcPArSZKkxnDwK0mSpMZw8CtJkqTGcPArSZKkxnDwK0mSpMYYaJ3fbg17zc66a5IO0vj4lgKlKaWW20F59dVXAdhpp522u120M+e8ze1jP9H+sbHt/z64o8fttWh/3HZq56D0u09aG1vaWr8/y+ru13W/Lwyy/vaw1zQe9ms92Ws5HJ+gkiRJ0gCMVPIrhTJ5bZdElwlpbNduP6Fd0jroxFeSJPWWya8kSZIaw+RXIykS3Ehk47ZMbCMBjvtl8lsmxbFdaJccD8ucW0mS9Pr4CS5JkqTGMPnVSCqT1zLZLefmRrL7hjds/yUf20VVhzjOjlaDkCRJw81PckmSJDXGQJPfftfu63e9uWGvE9xkkcy2q8bQbq5uu8et6rBFv/vMsNeQtA6w6lD367bfdXS7Vff5DZNRWh9gmJj8SpIkqTGc86uRFHNyN2/eDMC0adOAKrH905/+1LJd3H/ppZda9jNz5kygmgscz4/7nY4jSZJGi8mvJEmSGsPkVyMpqjvMmDGj5fH77rsPgDvuuAOANWvWALBu3brt7m+vvfYC4L3vfS8Ap5xyCgDHHnsssHWiLEmSRpPJryRJkhrD5FcjKebk/uIXvwDg8ssvB2DVqlUALFiwAIBPfOITAMybNw+AffbZp2U/v/vd7wD49a9/DcDtt98OwNKlSwE4+uijAbjwwgsBOPTQQ3t9KpIkaYBMfiVJktQYKeZODsLCsSV9Pdio1xHu9/NXjn8vbXeD12F8fDxDVV83brsVr8fYX1RZiDq8Mfc25vZ+6lOfAmDu3LkAXHbZZQAccMABLc8rqzW88sorAOy8884tx9+wYQMAzz77LFAlx5EMX3/99QAcc8wxLe2NqhCdVpCbrDhO3I6NjfXkf3inPll3ndu6+1Qn3e5/bM7anvfJ0KlPtvv5662JXfbZurRrx+s9n3J/nY4XetUnof+fld2q+7Osk6H6rHx67nav5bDX4a37Wnf7Ht3uPdbkV5IkSY3hnF/VYtOmTS33p0+fDlSpTaQqkdSG1atXA/DBD34QgNmzZwOwfPlyAHbZZRegqsoQqU6Z0pSJb6RAs2bNamnPG9/4RgB++9vfAnDeeecBcO211wJVNYh2iW8kwnEbybV1gjVsyj5TJqNlX+r1tz7dKtvxmm9JWh6P8wpx3v361kbS8DH5lSRJUmP4q65qEclqO2W6FMnrl770JQAWLlwIwD333APAsmXLALjuuuuAKsUpV2qLlCf2Hz8v5wZHshxzi++66y4AfvKTnwBw8cUXA/DWt74VgP333x/YOlUy6dWoiNdo9LkyCQ7xGo/to8/UnZxGe+PborKdIR6P9g5Lci1pcEx+JUmS1Bgmvxoq7f4C+7vf/S4ATz31FAC/+tWvALj77ruBakW29evXA7BixQoANm7cCGw9x7ecvxi3J598MgA//vGPAbjtttsAOOmkk4Bqju/8+fMBuOmmmwC46KKLAFMkja6yYkmZ5EaFlDJJjfuDrBy0LWW7oj1lZZfyvPpdqUXS8DH5lSRJUmMM9FfdftfUHPbagt0a9nqAk9Gujm/4wx/+AFQrr0Vd39hu0aJFQJXQnn766QB84AMfaHle7D+S4Eh54v6SJUsAWLlyJVAlyjG3OESadMEFFwBwww03ANWc4zlz5mxz+/IvyoclIa77Ndvv94S6da4nOqCG7IB2SW88Xn57En3zBz/4AQBf/vKX+93E7frCF74AwOLFiwF485vfDLSf998uCR4Fddde7VbddXwHWb+87nOte//DWgfY5FeSJEmNMXq/8mpK6ZSEPvzwwwA88cQTAJxzzjlAVSc4nh8J8A9/+EOgqtZw1llnAXD11VcDVRr0xz/+sWV/P/rRj4AqKT7xxBO32Z6oIxz7/cpXvgLAo48+Cmyd/MZ5DVviK5XK+fZl0ht9Liq1RF86/vjjATj88MMH0s52dt11V6BqVyjb3a76Q7uV3iRNPfZ2SZIkNYbJr2oR8+/KVaJiDnDU6vzNb34DwNve9jYAdtttt23uL54XVRliHmLM/4t5fldddRUAn/70pwG44447WraPqhGxfShXuYqUKer7RkL9vve9b5vnUVaVMGXSsGm3gluI5LRcrTD6Zt3VHsr2Rjvb1RS3L0rNZa+XJElSY5j8qhaRGpUropUpzOOPPw7AO97xDmDr1Km8H2nOaaedBlQrwJ1xxhkAvPOd7wTgxRdfBKoV24488siW9kSKVM4PjEQ4fj5v3jwAHnnkkZbtyr8gLxNuadiUc2ND2cfa9b1h0a5d5ePRF9udt6Spy+RXkiRJjTFUye+o1+zstnbgKNUu7FYktJHGlHV+I40plWlOzK0t/zI9Etyo9/ue97wHqFZuK5VzdNutZhWJbplYR2pU1vMN8Xjsf1jU3ef6ffx+94m666W+VrtvFXb024byW5dOc3ijD5RJat3KdpXKOc3t5vy2O592c6JVqbt27DAZpveIyRj29k+2lrrJryRJkhpjqJJfNUekM5GERgIcj0eSGvdffvnllufH/ai7W6YxkdyeffbZQJX4XnrppQCsWrUKgKOOOgqAu+66C6iS4kiSI4GO/UeaFMluJMbx8zIZjlRp2BJfqZNy3nvZR4f1NR3t6rR6pKTmMvmVJElSY5j8qhbtUpgyTYo6ug8++CBQzZ2NxDfuR8ozY8YMoKr2sGLFCgDuvPNOAI477jgALrzwQqCq6xsrwt1yyy0AfOhDH2rZ78yZM1vaFUnvk08+CcChhx7a8nNrh2rUtJunHuI1X/bRqHTywgsv9LF1ne2+++4AHHjggcDWCXA5hznOtzxvSVOfn9CSJElqDH/lVa06VUeYP38+AF/96leBKl2KlKdMb4444ggA1qxZA8D3v/99oEp2y5XWbr75ZgDOPfdcAJYuXQpU8xvPPPNMYOtaoM8//zxQpV6HHXYYUM01LqtPRPoU7fQvxTVsynnq7Wpdh9///vcA/PSnPwXgkksu6XcTt+uLX/wiUK2+uPfeewNbJ9XRt0N53pKmPnu7JEmSGiMNcj32hWNLujpYtzU7u61HV3e9u26Pv3L8ez2LG8fHxzNMfuWyMvGN12GZwqxfvx6Ao48+GoDPfOYzAJx33nkt+zn++OOBKvG94YYbAFiyZEnLfstkNo6zceNGAE466SQAHnjgAQCuu+46oJoDHNvH41deeSUAq1evBqrUqVwpLm4nuypWmViPjY315FqOPz13cG8ANai7z3d6/tictT3rk7nNm/lkv2Uo+2i7hLT8VqMu7Wppl+1u923Tjmr3mZl6+HVOt5+Vw67umvaD/Kzs97Wse1zSSd3Xut17rMmvJEmSGsM5v6pFmbqUoUnc32OPPYBqTu4VV1wBwIIFC4Bqnl8ktTfddBMAixcvBqqkN9Kgsi5wzOWN9tx7771AVe835gBHFYlFixYB8PWvfx2A888/H6gS3/CahLblvrVGNazKb0XKPhqv5XK7YVnhrexb7ebfl+fVbjtJU5fJryRJkhrD5Fe1KufflelNpEnLli0DqpXYYo7vM888A8CNN94IwKmnntry/NhvOU8x5vhGElyuGBf1gU844QQAPvKRj7Qcd8899wTgYx/7GFDNKwzlecS8yKgWIQ2bcv59zE8vqz6UCWndiW8o21G2M86n3WqNkprD5FeSJEmN4a+8qkUkpZG6RCpT1hiNRDaS1q997WtAlcB++MMfBqo5vvH82H+kO+VffEfCWybAZRIdK8PFqlGRCEd1hzlz5gCwYcMGAGbNmrXN843EN1KnYUnLpBB9JfpimYiWFVniNVzOa69LtCfaV867L7+NmWzlFUmjz+RXkiRJjTFUdX67rec26vpdj2+Y6vx2a9WqVQB88pOfBGDfffcF4PLLLwfgoIMOArZOf9rVKi0T34ceegiAz33ucwCsW7cOgMsuuwyAhQsX9vR8OulXnd9u+2S3NRr7/fx+G6ba28CUrg07AgZWG7bumvd16/f7wijV+e2k3/+v6n6Pn2wtdZNfSZIkNYZzfjWSYsW3b3/72wB84xvfAKq5wPHzqMu73377ATB37lygSqrXrl0LwGOPPQbA3XffDcB9990HwPvf/36gmmt88MEH9+V8JEnSYJj8SpIkqTFMfjWSYo7uYYcdBsDy5csBuP/++wG49dZbAbjmmmsAeO6554CqekTMnZ05cyZQrSR3yCGHtOzvmGOOAdqvbiVJkkaLya8kSZIaw+RXIymqMkQSO23aNACOPfbYltv4eSTFZfIb9X3j+e1WhTLxlSRpajD5lSRJUmMMNPmtu45vv+vZ1W3Y29dL7VZUK1dtKldvmj17dsv9WOGt0+pPcdtpJbdRM+w1GrvV7xqXo14vVVNT3f227vrdw14fXJW6roXJryRJkhrDOb8aSZG8btq0Cdg6oS1Xcos5wqUZM2a0bF+u9BaPx5zfqZL4SpLUVCa/kiRJagyTX42kmJM7ffp0ADZv3rzNx0NUd4jtIiGOld4iIY7b2E/cj6oQsZ94niRJGi0mv5IkSWoMk1+NpEhgQ5nchrJqQ7tEuJzrW1Z/iO1MfiVJGm0mv5IkSWqMgSa/ddfWs+Zn75QJ66CV1RvKpLbT4yES3HbVIMrt6kp86z5+O/2u4zvs9UI7adJ7ggan7s+qfvf7Ye/XqvT7Pa7b18LK8W0/bvIrSZKkxnDwK0mSpMZw8CtJkqTGcPArSZKkxnDwK0mSpMZw8CtJkqTGcPArSZKkxphSK7z1u7Zgv5/f79qJUqnuOrp114jsxD6pYdRtv+x3v+6k33V6O+1/srVhJ2PU/1/XrV/vwSa/kiRJagwHv5IkSWoMB7+SJElqjCk151fNkXOu9fgppVqPL0mSJsfkV5IkSY1h8quRZPIrSZImw+RXkiRJjZHqTtAkSZKkQTH5lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJjOPiVJElSYzj4lSRJUmM4+JUkSVJj/D828hIImkpbCwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#随机矩阵与矩阵相乘\n",
    "\n",
    "#准备所乘矩阵\n",
    "a=np.random.rand(12,12)\n",
    "x=a>0.5\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "\n",
    "for i in range(0,6):\n",
    "    #准备随机矩阵\n",
    "    d=np.random.rand(12,12)\n",
    "\n",
    "    fig,axs=plt.subplots(nrows=1, ncols=6, figsize=(12, 6))\n",
    "\n",
    "\n",
    "\n",
    "    dd=d>0.5\n",
    "    #矩阵与矩阵相乘的结果为res1\n",
    "\n",
    "    res1=otimes_bm_bm(dd,x)\n",
    "    #矩阵与转置后的矩阵相乘的结果为res2\n",
    "\n",
    "    res2=otimes_bm_bm(dd,np.transpose(x))\n",
    "    #绘图表达\n",
    "    axs[0].imshow(dd,vmin=0,vmax=1)\n",
    "    axs[0].set_title('A')\n",
    "    axs[0].set_axis_off()\n",
    "\n",
    "    axs[1].imshow(op)\n",
    "    axs[1].set_axis_off()\n",
    "\n",
    "    axs[2].imshow(x,vmin=0,vmax=1)\n",
    "    axs[2].set_title('x')\n",
    "    axs[2].set_axis_off()\n",
    "\n",
    "    axs[3].imshow(eq)\n",
    "    axs[3].set_axis_off()\n",
    "\n",
    "    axs[4].imshow(res1,vmin=0,vmax=1)\n",
    "    axs[4].set_title('res1')\n",
    "    axs[4].set_axis_off()\n",
    "\n",
    "    axs[5].imshow(res2,vmin=0,vmax=1)\n",
    "    axs[5].set_title('res2')\n",
    "    axs[5].set_axis_off()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#随机矩阵与转置矩阵相乘\n",
    "\n",
    "#准备所乘矩阵\n",
    "a=np.random.rand(108,108)\n",
    "x=a>0.5\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "\n",
    "\n",
    "\n",
    "fig,axs=plt.subplots(nrows=1, ncols=5, figsize=(12, 6))\n",
    "\n",
    "\n",
    "dd=x.transpose()\n",
    "\n",
    "#矩阵与矩阵相乘的结果为res1\n",
    "\n",
    "res1=otimes_bm_bm(dd,x)\n",
    "\n",
    "\n",
    "\n",
    "#绘图表达\n",
    "axs[0].imshow(dd,vmin=0,vmax=1)\n",
    "axs[0].set_title('A')\n",
    "axs[0].set_axis_off()\n",
    "\n",
    "axs[1].imshow(op)\n",
    "axs[1].set_axis_off()\n",
    "\n",
    "axs[2].imshow(x,vmin=0,vmax=1)\n",
    "axs[2].set_title('x')\n",
    "axs[2].set_axis_off()\n",
    "\n",
    "axs[3].imshow(eq)\n",
    "axs[3].set_axis_off()\n",
    "\n",
    "axs[4].imshow(res1,vmin=0,vmax=1)\n",
    "axs[4].set_title('res1')\n",
    "axs[4].set_axis_off()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#随机矩阵与向量相乘\n",
    "a=np.random.rand(1,3)\n",
    "x=a>0.5\n",
    "y=x[0].tolist()\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "\n",
    "for i in range(0,6):\n",
    "    d=np.random.rand(3,3)\n",
    "    fig,axs=plt.subplots(nrows=1, ncols=5, figsize=(12, 12))\n",
    "   \n",
    "    dd=d>0.5\n",
    "\n",
    "    res1=otimes_bm_bv(dd,y)\n",
    "    res=np.array([res1])\n",
    "    \n",
    "    #绘图表达\n",
    "    axs[0].imshow(dd,vmin=0,vmax=1)\n",
    "    axs[0].set_title('A')\n",
    "    axs[0].set_axis_off()\n",
    "    \n",
    "    axs[1].imshow(op)\n",
    "    axs[1].set_axis_off()\n",
    "    \n",
    "    axs[2].imshow(x,vmin=0,vmax=1)\n",
    "    axs[2].set_title('x')\n",
    "    axs[2].set_axis_off()\n",
    "    \n",
    "    axs[3].imshow(eq)\n",
    "    axs[3].set_axis_off()\n",
    "    \n",
    "    \n",
    "    axs[4].imshow(res,vmin=0,vmax=1)\n",
    "    axs[4].set_title('res')\n",
    "    axs[4].set_axis_off()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finded feature vector\n",
      "[False, True, False]\n",
      "[False, True, False]\n",
      "finded feature vector\n",
      "[True, False, True]\n",
      "[True, False, True]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ruZIkScqOSa4kSZKy4+MK6tGe+LhC9PbbbwPw4IMPlrE333wTgAkTJpSxuHvQoYceWsZGjx4N1D7T6tWry3OffPIJAIsWLSpjS5cuBeCss84C4I477ijPHXfccb/yk/QthxbViuxT7FOklJVcSZIkZcdKrnq0J1ZyGydxpP9OYtXlhRdeKGOrVq0C4JtvviljcUmh+NqhQ4eW5+I+9yeccEIZmzZtGgATJ04E6ieXxH3sBw8evKsfqU9ZdVErsk+xT5FSVnIlSZKUHZNcSZIkZcfHFdSjPfFxhSgO6Q0cOLCMVa1RGa9LdxtqHFqMOxKl96saKoy7KqX3apUhxcihRbUi+xT7FCllJVeSJEnZGdDzJdKeJ+7dXrVve6yKxL3lG4+jkSNH1v053We+6vrG+6bX7Kg9klqffYrU/6zkSpIkKTtWcqUKsbqxefNmoLrCEveRh9ozdem+8Y2GDBlSHsfXps/IxdfGc/GZvLQ9ktqTfYrU/6zkSpIkKTsmuZIkScqOjytIFeKEjUGDBgGwZcuW7Z5LpcvgxNfEoch0KaM4FJkuHRTvG2Pp8kDxvq22HJKk3rFPkfqflVxJkiRlx0quVKFxk5S0OlK1cHvVEkCNVZn0no372De+tvF6qy5Se7NPkfqflVxJkiRlxyRXkiRJ2fFxBTVN1RBdq2hcm7JqN6GdOQ/1w4I7Wvuy6vpWG1Js5bZpz2Wf0vvrW+3fbSu3Te2rdXsESZIkaReZ5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOwMaHYDpFZUFEWzm1AphNDsJkjaBfYpUv+zkitJkqTsmORKkiQpOz6uIFVwaFFSX7JPkfqflVxJkiRlJ7Tqb5eSJEnSrrKSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKjkmuJEmSsmOSK0mSpOyY5EqSJCk7JrmSJEnKzv8DhUq0PGUtMwUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#矩阵与随机向量相乘，寻找特征向量及特征值\n",
    "d=np.random.rand(3,3)\n",
    "\n",
    "dd=d>0.5\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "\n",
    "for i in range(0,6):\n",
    "    a=np.random.rand(1,3)\n",
    "    x=a>0.5\n",
    "    y=x[0].tolist()\n",
    "\n",
    "    fig,axs=plt.subplots(nrows=1, ncols=5, figsize=(12, 12))\n",
    "   \n",
    " \n",
    "\n",
    "    res1=otimes_bm_bv(dd,y)\n",
    "    res=np.array([res1])\n",
    "    \n",
    "    axs[0].imshow(dd,vmin=0,vmax=1)\n",
    "    axs[0].set_title('A')\n",
    "    axs[0].set_axis_off()\n",
    "    \n",
    "    axs[1].imshow(op,vmin=0,vmax=1)\n",
    "    axs[1].set_axis_off()     \n",
    "    \n",
    "    axs[2].imshow(x,vmin=0,vmax=1)\n",
    "    axs[2].set_title('x')\n",
    "    axs[2].set_axis_off() \n",
    "    \n",
    "    axs[3].imshow(op,vmin=0,vmax=1)\n",
    "    axs[3].set_axis_off()\n",
    "    \n",
    "    axs[4].imshow(res,vmin=0,vmax=1)\n",
    "    axs[4].set_title('res')\n",
    "    axs[4].set_axis_off() \n",
    "    \n",
    "    if y==res1:\n",
    "        print('finded feature vector')\n",
    "        print(y)\n",
    "        print(res1)\n",
    "    else:\n",
    "        if y==otimes_bv_b(res1,False):\n",
    "            print('finded rev feature vector')\n",
    "            print(y)\n",
    "            print(res1)     \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#准备卷积矩阵，并转换为向量\n",
    "va=np.random.rand(3,3)\n",
    "vx=va>0.5\n",
    "vy=vx.flatten().tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "vy=[False,True,False,True,True,True,False,True,False]\n",
    "vx=np.array(vy)\n",
    "vx=vx.reshape((3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "vy=[True,True,True,True,True,True,True,True,True]\n",
    "vx=np.array(vy)\n",
    "vx=vx.reshape((3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0xb546eb0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(vx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#矩阵类似卷积计算\n",
    "\n",
    "#准备矩阵\n",
    "d=np.random.rand(9,9)\n",
    "\n",
    "dd=d>0.5\n",
    "\n",
    "x=np.vsplit(dd, 3)\n",
    "\n",
    "y=[np.hsplit(a,3) for a in x]\n",
    "\n",
    "#y[0][0]\n",
    "\n",
    "#y[0][1].flatten().tolist()\n",
    "\n",
    "#准备子矩阵\n",
    "temp=[y[i][j] for i in range(0,3)\n",
    "     for j in range(0,3)]\n",
    "\n",
    "\n",
    "\n",
    "#计算出类似卷积结果矩阵（4x4）\n",
    "res=[otimes_bv_bv(u.flatten().tolist(),vy) for u in temp  ]\n",
    "\n",
    "res=np.array(res).reshape((3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cAAAARIckFwiwjmGzZ8+WJK1bt86te/fddyVJr7/+uit79tlnJUm//PKLK7NhyqxjVktLi1s3bdo0SdLZZ5/tyuwY8+bNk5TssGZzwzMvPAAA5SHJBQAAQHSo5AIAACA6NFcAAmz8WmsmMGnSJLdu/vz5iT/97fwZzNLNFWyWM39/oeYHNouQ7XO07QAAwOhIcgEAABAdklwgYGhoSJLU2tpatC40X3to7vbp06cn/j48PFxy+/R+/W1KnQ8AAChGkgsAAIDokOQCAZaY7tu3T1I4tc3n867Mhvuytrwhzc3Nbtk+67fhtc/aOr9NLgkuAACVyUwlt29wYKJPYUKN1/V3t3dW/Jmt+bG3AQAAyBKaKwAAACA6mUlygSyxTmCTJ0+WJO3fv3/UdT4bLsz/jDVvyOVybp01b/BnNbP9Wpk/5Jjt198HAAAYHUkuAAAAokOSCwT4iayUTFz9ZRMaViyd9Pr7tA5nfke19LBi/vYkuQAAVIYkFwAAANGhkgsAAIDo0FwBEyb02j8r0uPdhmYoq2S9lGxqUGo83dD2WWumkOVzAwBAIskFAABAhKjkAgAAIDpUcgEAABAdKrkAAACIDpVcAAAARKehR1fobu8cl+P0DQ5UtH0151XpMcbzOAAAAI2GJBcAAADRoZILAACA6FDJBQAAQHSo5AIAACA6VHIBAAAQHSq5AAAAiA6VXAAAAESnocfJBeplZGRkok8hKJfLTfQpAADQEEhyAQAAEB0quQAAAIgOzRWAAJorAADQ2EhyAQAAEJ1cVhMrAAAAoFokuQAAAIgOlVwAAABEh0ouAAAAokMlFwAAANGhkgsAAIDoUMkFAABAdKjkAgAAIDpUcgEAABAdKrkAAACIDpVcAAAARIdKLgAAAKJDJRcAAADRoZILAACA6FDJBQAAQHSo5AIAACA6VHIBAAAQHSq5AAAAiA6VXAAAAESHSi4AAACiQyUXAAAA0aGSCwAAgOhQyQUAAEB0qOQCAAAgOv8BgsIwuuYlz4kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#输出：原始矩阵，类似卷积矩阵，类似卷积结果\n",
    "op=imread('op.jpg')\n",
    "eq=imread('eq.jpg')\n",
    "\n",
    "fig,axs=plt.subplots(nrows=1, ncols=5, figsize=(12, 6))\n",
    "axs[0].imshow(dd,vmin=0,vmax=1)\n",
    "axs[0].set_axis_off()\n",
    "axs[1].imshow(op,vmin=0,vmax=1)\n",
    "axs[1].set_axis_off()\n",
    "\n",
    "axs[2].imshow(vx,vmin=0,vmax=1)\n",
    "axs[2].set_axis_off()\n",
    "\n",
    "axs[3].imshow(eq,vmin=0,vmax=1)\n",
    "axs[3].set_axis_off()\n",
    "axs[4].imshow(res,vmin=0,vmax=1)\n",
    "axs[4].set_axis_off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
